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Ann Surg. 2016 Oct;264(4):621-31. doi: 10.1097/SLA.0000000000001855.

Postoperative 30-day Readmission: Time to Focus on What Happens Outside the Hospital.

Author information

1
*Birmingham and Tuscaloosa Health Services Research & Development Unit, Birmingham VA Medical Center, Birmingham, AL †Department of Surgery, University of Alabama at Birmingham, Birmingham, AL ‡VA Boston Healthcare System, Boston, MA §Boston University School of Medicine, Department of Surgery, Boston, MA ¶Harvard School of Medicine, Cambridge, MA ||Veterans Affairs, Center for Healthcare Organization and Implementation Research (CHOIR), VA Boston Healthcare System, Boston, MA **Veterans Affairs: Central Texas Veterans Health Care System, Baylor Scott & White Health, Center for Applied Health Research, Temple, TX ††Texas A&M Health Science Center, College of Medicine, Temple TX ‡‡Veterans Affairs, Milwaukee VAMC, Milwaukee, WI §§Department of Surgery, VA Pittsburgh Healthcare System, Pittsburgh, Pennsylvania ¶¶Veterans Affairs, Palo Alto VAMC, Palo Alto, CA ||||Department of Surgery, Stanford University School of Medicine, Palo Alto CA.

Abstract

OBJECTIVE:

The aim of this study is to understand the relative contribution of preoperative patient factors, operative characteristics, and postoperative hospital course on 30-day postoperative readmissions.

BACKGROUND:

Determining the risk of readmission after surgery is difficult. Understanding the most important contributing factors is important to improving prediction of and reducing postoperative readmission risk.

METHODS:

National Veterans Affairs Surgical Quality Improvement Program data on inpatient general, vascular, and orthopedic surgery from 2008 to 2014 were merged with laboratory, vital signs, prior healthcare utilization, and postoperative complications data. Variables were categorized as preoperative, operative, postoperative/predischarge, and postdischarge. Logistic models predicting 30-day readmission were compared using adjusted R and c-statistics with cross-validation to estimate predictive discrimination.

RESULTS:

Our study sample included 237,441 surgeries: 43% orthopedic, 39% general, and 18% vascular. Overall 30-day unplanned readmission rate was 11.1%, differing by surgical specialty (vascular 15.4%, general 12.9%, and orthopedic 7.6%, P < 0.001). Most common readmission reasons were wound complications (30.7%), gastrointestinal (16.1%), bleeding (4.9%), and fluid/electrolyte (7.5%) complications. Models using information available at the time of discharge explained 10.4% of the variability in readmissions. Of these, preoperative patient-level factors contributed the most to predictive models (R 7.0% [c-statistic 0.67]); prediction was improved by inclusion of intraoperative (R 9.0%, c-statistic 0.69) and postoperative variables (R 10.4%, c-statistic 0.71). Including postdischarge complications improved predictive ability, explaining 19.6% of the variation (R 19.6%, c-statistic 0.76).

CONCLUSIONS:

Postoperative readmissions are difficult to predict at the time of discharge, and of information available at that time, preoperative factors are the most important.

PMID:
27355263
DOI:
10.1097/SLA.0000000000001855
[Indexed for MEDLINE]

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